📊
Data

A/B Test Analysis

by phuryn

A/B Test Analysis is a Data skill for Claude Code, published by phuryn in pm-skills.

25.2K stars2.7K forkson phuryn/pm-skillsAdded 2026/08/14Repository updated 2026/07/03
agent-skill-repositoryagent-skillsagentic-skillsclaude-code-marketplaceclaude-code-pluginsclaude-cowork-pluginproduct-management
Install in seconds
Install A/B Test Analysis
Copy A/B Test Analysis into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/phuryn/pm-skills/tree/main/pm-data-analytics/skills/ab-test-analysis ~/.claude/skills/ab-test-analysis

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/phuryn/pm-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
pm-data-analytics/skills/ab-test-analysis/SKILL.md in phuryn/pm-skills
Installs to
~/.claude/skills/ab-test-analysis
Collection
One of 25 skills cataloged from this repository
Category
Data668 skills

What A/B Test Analysis does

A/B Test Analysis evaluates A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when interpreting split test data, checking if a test reached significance, or deciding whether to ship a variant.

A/B Test Analysis is cataloged under Data on DirSkills. A/B Test Analysis comes from a repository tagged agent-skill-repository, agent-skills, agentic-skills, claude-code-marketplace and claude-code-plugins.

Documentation

README

A/B Test Analysis

Evaluate A/B test results with statistical rigor and translate findings into clear product decisions.

Context

You are analyzing A/B test results for $ARGUMENTS.

If the user provides data files (CSV, Excel, or analytics exports), read and analyze them directly. Generate Python scripts for statistical calculations when needed.

Instructions

  1. Understand the experiment:
    • What was the hypothesis?
    • What was changed (the variant)?
    • What is the primary metric? Any guardrail metrics?
    • How long did the test run?
    • What is the traffic split?

This is the opening of the README. Read the full README on GitHub.

Frequently asked about A/B Test Analysis

  • What else does phuryn publish alongside A/B Test Analysis?

    A/B Test Analysis is one of 25 skills that DirSkills catalogs from phuryn/pm-skills, the repository it ships in. Its siblings there include Beachhead Segment, Brainstorm Team OKRs and Cohort Analysis. Each one is a separate skill with its own page in this directory, installs the same way A/B Test Analysis does, and is maintained by phuryn in that same repository. The rest of the collection is listed on the phuryn/pm-skills page.

  • How does A/B Test Analysis compare to other Data skills?

    A/B Test Analysis ranks #68 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of A/B Test Analysis against them. Open each page to compare what they document and how they install.

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